**Autonomous Mobile Robot Localization Challenge: "The Maze

Autonomous Mobile Robot Localization Challenge: "The Maze of Variability"

Scenario:

You are tasked with developing an autonomous mobile robot that can accurately localize itself within a dynamic maze of variable geometry. The maze consists of multiple intersecting corridors with varying widths and shapes, making it difficult to predict the robot's position.

Constraints:

1. Limited Sensor Suite: Your robot is equipped with a single monocular camera, a GPS receiver (with occasional signal loss), and an Inertial Measurement Unit (IMU).
2. Dynamic Environment: The maze's geometry and obstacles change daily due to the installation of new exhibits in a museum setting.
3. Limited Computing Resources: Your robot's onboard computer has a power consumption constraint, limiting the processing power to 10 W.
4. Real-time Requirements: The robot must continuously localize itself in real-time, updating its position estimate every 10 seconds.

Challenge Objectives:

1. Accurate Localization: Develop a localization algorithm that can accurately estimate the robot's position in the maze, even in areas with poor visibility or GPS signal loss.
2. Efficient Processing: Design a lightweight and computationally efficient algorithm that meets the power consumption constraint.
3. Robustness to Changes: Demonstrate the ability of your algorithm to adapt to changes in the maze's geometry and obstacles.

Evaluation Criteria:

• Localization error (position estimate accuracy)
• Processing power consumption
• Robustness to changes in the maze
• Real-time performance

Submission Requirements:

• A detailed technical report documenting your approach, algorithm, and implementation
• A video demonstrating the robot's performance in the maze
• A dataset of the maze's geometry and obstacle layout for testing and evaluation

Submission Deadline: 31 March 2026

Prizes:

• A research grant to further explore the use of autonomous systems in museum settings
• Public recognition and publication of your work in a top-tier robotics conference

Join the challenge and showcase your expertise in autonomous systems and AI!

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Publicado automáticamente con IA/ML.